🔥 PDF Document Translator MCP Server - Complete Implementation

[codegen-sh]

📄 PDF Document Translator MCP Server

A complete MCP (Model Context Protocol) server implementation that translates PDF documents using AI vision models, built following the Hugging Face MCP course guidelines.

🚀 Key Features

• PDF Processing: Converts PDF pages to high-quality images (300 DPI)
• AI Vision OCR: Extracts text using Hugging Face vision models
• Multi-language Translation: Supports 12+ languages (EN, ES, FR, DE, IT, PT, RU, ZH, JA, KO, AR, HI)
• MCP Server: Functions as both web interface and MCP server for AI assistants
• Gradio Integration: Uses mcp_server=True for automatic MCP tool generation
• HF Spaces Ready: Complete deployment configuration included

🛠️ Technical Implementation

• Framework: Gradio with MCP support
• PDF Processing: PyMuPDF for high-quality conversion
• AI Models: Hugging Face transformers for vision and translation
• Architecture: Follows MCP course best practices
• Error Handling: Comprehensive error handling and validation

📁 Project Structure

├── app.py                 # Main MCP server application
├── requirements.txt       # Dependencies
├── config.json           # HF Spaces configuration
├── README.md             # Comprehensive documentation
├── DEPLOYMENT.md         # Deployment guide
├── test_app.py           # Test suite
├── examples/
│   └── sample_usage.py   # Usage examples
└── .gitignore           # Git ignore rules

🌐 Usage

Web Interface: Upload PDF → Select languages → Get translations
MCP Tool: document_translator(pdf_file, source_lang, target_lang)

🚀 Deployment

Ready for immediate deployment to Hugging Face Spaces:

1. Create new Gradio Space
2. Upload project files
3. MCP endpoint: https://your-space.hf.space/gradio_api/mcp/sse

🧪 Testing

Includes comprehensive test suite covering:

• PDF processing functionality
• Text extraction and translation
• Error handling scenarios
• MCP server integration

📚 Documentation

• Complete README with usage examples
• Detailed deployment guide
• Sample configurations for Claude Desktop
• Language code reference

This implementation demonstrates practical application of the HuggingFace MCP course concepts with a real-world document translation use case.

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